Internal Design of a Hydroponics Greenhouse for Tri Cycle Farms

Hydroponics is the agricultural technique of growing plants without soil, using other growing media and added nutrients in a solvent. It is an attractive agricultural method over conventional agriculture because it is more water efficient, is less labor intensive, yields higher quality crops in less time, and is easier to control. According to the Digital Journal, “hydroponics crop value is anticipated to grow to USD 27.29 Billion by 2022 at an estimated CAGR of 6.39% from 2015 to 2020” (Sawant, 2016). Alongside this growing market acceptance for hydroponics, there is also a local demand that requires only a small transportation cost. For the past several years, Tri Cycle Farms - a 501-(c)(3) non-profit urban farm in Fayetteville - has dreamt of building a hydroponics greenhouse because it would provide a source of sustainable financial income, a location for educational programming, and a means of battling food insecurity. Since August 2017, I have been working with Tri Cycle Farms to help make the hydroponics greenhouse project a reality. The objectives of this section of the overall project are 1) to determine desirable crops to be produced, 2) design the internal layout of the chosen greenhouse, and 3) design one hydroponics system using engineering design and fluid mechanics. This thesis report outlines the process of fulfilling these objectives, the justification behind the design decisions, and a discussion of the potential implications moving forward

Beyond the RPA on the cheap: improved correlation energies with the efficient "Radial Exchange Hole" kernel

The "ACFD-RPA" correlation energy functional has been widely applied to a variety of systems to successfully predict energy differences, and less successfully predict absolute correlation energies. Here we present a parameter-free exchange-correlation kernel that systematically improves absolute correlation energies, while maintaining most of the good numerical properties that make the ACFD-RPA numerically tractable. The "RXH" kernel is constructed to approximate the true exchange kernel via a carefully weighted, easily computable radial averaging. Correlation energy errors of atoms with two to eighteen electrons show a thirteenfold improvement over the RPA and a threefold improvement over the related "PGG" kernel, for a mean absolute error of 13mHa or 5%. The average error is small compared to all but the most difficult to evaluate kernels. van der Waals $C_6$ coefficients are less well predicted, but still show improvements on the RPA, especially for highly polarisable Li and Na

Self-Lensing By A Stellar Disk

I derive a general expression for the optical depth $\tau$ for gravitational lensing of stars in a disk by Massive Compact Objects (Machos) in the same disk. For the more restricted case where the disk is self-gravitating and the stars and Machos have the same distribution function, I find \tau = 2\VEV{v^2}/c^2\sec^2 i where \VEV{v^2} is the mass-weighted vertical velocity dispersion, and $i$ is the angle of inclination. This result does not depend on any assumptions about the velocity distribution. As an example, if stars within the bar of the Large Magellanic Cloud (LMC) account for the observed optical depth $\tau\sim 8\times 10^{-8}$ as has recently been suggested, then v\gsim 60\,\kms. This is substantially larger than the measured dispersions of known LMC populations.Comment: 6 pages, no figures, phyzzx macro package, or request PostScript file to [email protected], OSU-TA-13/9